In conventional image projection systems, there is generally a single projector projecting a single image. Such an image may be projected forward or backward, according to the type of projector used.
It is known to use the concept of a "video wall" to project multiple images, or to project portions of a single image arranged to simulate the look and feel of a larger image. For example, nine televisions (video displays) are disposed within a single wall in a three-by-three matrix. Each television displays the same image, or displays one-ninth of a scene. The effect of the latter is that the scene appears to be the dimension of the nine television displays, although interrupted by the spacing between each television. Other approaches project multiple images on a wall, and by overlapping and performing image processing on the images such as averaging, to give the appearance of continuity. Other multiple image displays simply leave gaps of about a quarter inch between the neighboring images.
Multiple image displays may be required in cases typically encountered in image processing, where datasets are too large to display using one video display. For example, a physician or analyst may need to view a large dataset that exceeds hardware framing limitations. When examining such a large dataset across multiple image displays, the physician or analyst typically encounters problems in examining the importance of the data in the mullions between neighboring images. In this scenario, the analyst requires additional contextual cues in displaying multiple images to adequately infer, deduce or conclude, including the ability to view such data seamlessly from one image to the next.
In systems such as information visualization and management, where seamlessness between multiple images provides significant advantages, a problem arises when the need to access information in adjacent images is disrupted by a mullion in the information such as averaged or missing data between the images. These circumstances exist when there is an image overlap, or even a black gap. Thus, when a user of the image displaying data needs to move between these images, his/her ability to integrate, infer, deduce, and conclude is disrupted by such interruptions between images.